Text Generation
fastText
Uzbek
wikilangs
nlp
tokenizer
embeddings
n-gram
markov
wikipedia
feature-extraction
sentence-similarity
tokenization
n-grams
markov-chain
text-mining
babelvec
vocabulous
vocabulary
monolingual
family-turkic_other
Instructions to use wikilangs/uz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastText
How to use wikilangs/uz with fastText:
from huggingface_hub import hf_hub_download import fasttext model = fasttext.load_model(hf_hub_download("wikilangs/uz", "model.bin")) - Notebooks
- Google Colab
- Kaggle
Download visualizations/tsne_sentences.png from wikilangs/uz: direct link, hf CLI and curl.
- Browser
- Download file 281 kB
-
https://huggingface.co/wikilangs/uz/resolve/main/visualizations/tsne_sentences.png
- Command line
-
hf download hf://wikilangs/uz/visualizations/tsne_sentences.png
-
curl -L -o tsne_sentences.png https://huggingface.co/wikilangs/uz/resolve/main/visualizations/tsne_sentences.png
281 kB

- Xet hash:
- 7d5896218e3e8a91840bad11141bd849c266dd327f8d9f28c11798b531a4c696
- Size of remote file:
- 281 kB
- SHA256:
- c6bb2260aca237e8f32abef66fc055e002d6011a7d2e5bfbe3889a93be7799af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.